Data Supplement to EPA 840-B-22009 Development and Evaluation of the Beta Streamflow Duration Assessment Method (SDAM) for the Great Plains (GP)


September 2022
EPA-840-R-22Q03

of the Beta
Streamflow Duration Assessment Method
(SDAM) for the Great Plains (GP)

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Development and Evaluation of the Beta
Streamflow Duration Assessment Method
for the Great Plains

Data analysis supplement

Michele Eddy
RTI International

Research Triangle Park, NC 27709
Ken Fritz

Office of Research and Development
Cincinnati, OH 45268

Shannon Gross
RTI International
Fort Collins, CO 80528

Brian Topping

Office of Wetlands, Oceans, and Watersheds
Washington, DC 20004

Tracie-Lynn Nadeau Rachel Fertik Edgerton

Office of Wetlands, Oceans, and Watersheds Office of Wetlands, Oceans, and Watersheds

Portland, OR 97205 Washington, DC 20004

Julie Kelso, ORISE Fellow (former)

Office of Wetlands, Oceans, and Watersheds

Washington, DC 20004

This document has been reviewed in accordance with U.S. Environmental Protection Agency
policy and approved for publication. This report fulfills EPA QA requirements. The research for
the data was conducted under the Office of Water approved Quality Assurance Project Plan
"Streamflow Duration Assessment Method (SDAM) development in the Great Plains (GP) and
Western Mountains (WM)" which was given an ORD ID of J-WECD-0033408-QP-1-0. Any mention
of trade names, manufacturers or products does not imply an endorsement by the United States
Government orthe U.S. Environmental Protection Agency. EPA and its employees do not endorse
any commercial products, services, or enterprises. Funding was provided under contracts EP-C-
17-001 and 68HERC21D0008 for data management and analysis, respectively, and EP-C-16-006
for data collection. The views expressed in this report are those of the authors and do not
necessarily represent the views or policies of the U.S. Environmental Protection Agency.

Suggested citation: Eddy M., Gross, S., Fritz, K.M., Nadeau, T.-L., Topping, B., Fertik Edgerton, R.,
and Kelso, J. 2022. Development and Evaluation of the Beta Streamflow Duration Assessment
Method for the Great Plains. Document No. EPA-840-R-22003.

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Introduction

Streamflow duration assessment methods (SDAMs) are rapid, field-based methods to determine
flow duration class at the reach scale. The development of a beta SDAM for the Northern and
Southern Great Plains regions (hereafter referred to as the GP) followed the conceptual
framework and process steps presented by Fritz and others (2020) to integrate the three key
components of an SDAM development study: hydrological data, indicators, and study reaches.

This supplemental document describes the data collection, data analysis, and evaluation steps
that resulted in the beta SDAM for the GP. This document is available to inform public review and
comment on the beta method, as well as serving as a companion to the beta SDAM GP for those
that are interested in more background on the development of the method and the underlying
data. For a complete description of the beta SDAM GP protocol, please see the User Manual
(https://www.epa.gov/svstem/files/documents/2022-09/beta-sdam-for-the-gp-user-
manual.pdf). The data used to develop the beta SDAM GP can be found here:
(https://doi.org/10.23719/1527943). For more information on the collaborative effort between
the U.S. Environmental Protection Agency (EPA) and the U.S. Army Corps of Engineers (Corps) to
develop regional SDAMs for nationwide coverage, please see: https://www.epa.gov/streamflow-
duration-assessment.

Streamflow Duration Classes

Streamflow duration governs important ecosystem functions (such as support for aquatic life,
sediment transport, and biogeochemical processing rates), and streamflow duration classes are
often used to guide watershed management decisions, including assessing the applicability of
water quality standards. Our definitions of streamflow duration classes follow those used by
Nadeau (2015):

• Ephemeral reaches flow only in direct response to precipitation. Water typically flows
only during and/or shortly after large precipitation events, the streambed is always
above the water table, and stormwater runoff is the primary water source.

• Intermittent reaches contain sustained flowing water for only part of the year, typically
during the wet season, where the streambed may be below the water table or where
the snowmelt from surrounding uplands provides sustained flow. The flow may vary
greatly with stormwater runoff.

• Perennial reaches contain flowing water continuously during a year of normal rainfall,
often with the streambed located below the water table for most of the year.
Groundwater typically supplies the baseflow for perennial reaches, but the baseflow
may also be supplemented by stormwater runoff or snowmelt.

For these definitions, a reach is a section of stream or river along which similar hydrologic
conditions exist (e.g., discharge, depth, velocity, or sediment transport dynamics) and
consistent drivers of hydrology are evident (e.g., slope, substrate, geomorphology, or

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confinement). A channel is an area that is confined by banks and a bed and contains flowing
water (continuously or not).

Overview of the Beta Method for the Great Plains

The beta SDAM GP uses a small number of indicators to predict the streamflow duration class of
stream reaches. All indicators are measured during a single field visit. The beta SDAM GP results
in one of four possible classifications: ephemeral, intermittent, perennial, or at least intermittent.
The latter category occurs when an intermittent or perennial classification cannot be made with
high confidence, but an ephemeral classification can be ruled out.

The tool uses a machine learning model known as random forest (Figure 1). Random forest
models are increasingly common in the environmental sciences because of their superior
performance in handling complex relationships among indicators used to predict classifications.
This approach was previously used to develop regional SDAMs for the Pacific Northwest (PNW;
Nadeau et al. 2015, Nadeau 2015), Arid West (AW; Mazor et al. 2021a, Mazor et al 2021b), and
Western Mountains (WM; Mazor et al. 2021c; Mazor et al. 2022).

Set aside 20% for
testing

Sample from the original
training set with
replacement to create
independent subsamples

Build the trees on a
random subset of
features

Aggregate decisions

Majority voting

| Ephemeral Final Prediction

Figure 1. Random forest procedure used to determine a flow classification.

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Development of the Beta Great Plains SDAM

The specific data analysis steps described in this document follow the approach used to develop
and evaluate the beta SDAM WM (Mazor et al. 2022).

Study Area

The GP spans the central U.S. from Canada to Mexico and encompasses all or portions of 15 states
(Figure 2). It includes areas largely dominated by native prairie-type vegetation (tall, short, and
mixed grass) that generally receive less than 40 inches of precipitation a year. However,
significant forested areas are also found in the northeast part of the Northern GP region, where
average yearly rainfall totals are closer to the upper end of the range (30 to 40 inches). The GP
regions are divided into Northern and Southern GP regions based on the importance of snowmelt
to river discharge; the boundary between the two approximately follows the line south of which
mean annual snowfall is less than 0.7 m/y (<2 ft/y; Wohl et al. 2016). Ephemeral and intermittent
reaches may be found at any position within a watershed but are more common in smaller
headwaters, where flow accumulation is insufficient to sustain longer-duration flows. Ephemeral
and intermittent reaches are also generally more common in semi-arid parts of these regions,
where mean annual precipitation totals are lowest (10-20 inches), and evapotranspiration is
relatively high.

There are several large and/or growing metropolitan areas within or partially within the GP,
including Austin, Chicago, Dallas, Denver, Kansas City, Minneapolis, Milwaukee, and San Antonio.
Thus, there are places within the GP regions where the need for an SDAM in permitting and
management programs is particularly high. In addition, development associated with oil and
natural gas, as well as agricultural uses that may require more and/or modified water sources
due to climate change, occur across the GP (Vengosh et al. 2014, Perkin et al. 2017). Within a
portion of the Southern GP region, there is one SDAM currently in use, applicable to New Mexico
(New Mexico Environment Department [NMED] 2011).

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Alaska

Pacific
Northwest

Northern
Great Plains

Northeast

Western
Mountains

Arid
West

Southeast

Hawaii

Southern
Great Plains

Figure 2. Map ofSDAM study regions (based on Wohl et al. 2016). The beta SDAM GP applies to the Northern and Southern

Great Plains as shown.

Preparation and Candidate Indicators

At the outset of the project, we assembled a regional steering committee (RSC) consisting of
technical staff at Corps Districts and EPA Regional Offices in the GP region that manage
programs where streamflow duration information is often needed (e.g., Clean Water Act
programs, including permits and enforcement). RSC members were selected based on their
expertise in both scientific and programmatic elements relevant to streamflow duration
classification needs. The RSC served several functions in the development process, such as
reviewing technical products, facilitating connections with local experts, identifying resources
such as sources of hydrologic data, and providing input on the model selection.

We identified candidate indicators that were supported by the scientific literature (James et al.
2022) or used in the New Mexico SDAM (herein referred to as NM method; NMED 2011). In
addition, we included candidate indicators from the SDAM PNW (Nadeau 2015). Following
input from the RSC, these candidate indicators were then screened using the criteria described
by Fritz and others (2020), including:

Primary criteria

• Consistency: Does the indicator consistently discriminate among flow duration classes
(e.g., demonstrated in multiple studies)?

• Repeatability: Can different practitioners take similar measurements, given sufficient
training and standardization?

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•	Defensibility: Does the indicator have a rational mechanistic relationship with flow
duration, as either a response or a driver?

•	Rapidness: Can the indicator be measured during a one-day reach-visit (even if
subsequent lab analyses are required)?

•	Objectivity: Does the indicator rely on objective (often quantitative) measures, as
opposed to subjective judgments of practitioners?

Secondary criteria

•	Robustness: Does human activity complicate indicator measurement or interpretation
(e.g., poor water quality may affect the expression of some biological indicators)?

•	Practicality: Can practitioners realistically sample the indicator with typical capacity,
skills, and resources?

Candidate indicators were included in the study (Table 1) if they: 1) met all the primary criteria;
2) at least one of the secondary criteria; or 3) were included in the NM method (Level 1 only) to
facilitate comparison (because not all NM indicators met all primary criteria). Desktop
geospatial indicators (derived using a geographic information system and applicable spatial
datasets) that characterize mechanisms affecting flow duration and have been explored in
other flow duration classification tools (e.g., Eng et al. 2016, Jaeger et al. 2019, Mazor et al.
2021c) were also included in the analysis.

Table 1. Candidate indicators evaluated in the present study. Indicators with "NM" in the Origin column were measured following
the NM method protocol (NMED 2011) and indicators marked with "PNW" were measured following the PA/1/1/ protocol (Nadeau
2015); other indicators (OTH) were measured with protocols developed for this study (USEPA 2019) and derived from sources
resulting from a literature review completed by James et al. (2022) or recommendations from the RSC. Asterisks (*) indicate
hydrologic indicators that are considered direct measures of water presence.

Candidate indicator

Description

Origin

Geomorphic indicators



Sinuosity

Visual estimate of the curviness of the stream
channel

NM



Bankfull width

Width of the channel at bankfull height

PNW



Floodplain channel

Visual estimate of the extent of channel

NM



dimensions

entrenchment and connectivity to the floodplain





Particle size/stream substrate

Visual estimate of the extent of evidence of

NM



sorting

substrate sorting within the channel





Slope

Valley slope measured with a handheld
clinometer

PNW



In-channel structure/riffle

Visual estimate of the diversity and

NM



pool sequence

distinctiveness of riffles, pools, and other flow-
based microhabitats





Sediment deposition on

Visual estimate of the extent of evidence of

NM



plants and debris

sediment deposition on plants and on debris
within the floodplain



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Candidate indicator Description Origin

H

ydrologic indicators



Surface and subsurface flow*

Estimate of the percent of the reach-length with
surface and subsurface flow

PNW



Isolated pools*

Number of pools in the channel without any
connection to flowing surface water

PNW



Water in channel*

Visual estimate of the extent of surface flow in
the channel

NM



Seeps and springs*

Presence/absence of springs or seeps within one-
half channel width of the channel

NM



Hydric soils

Presence/absence of hydric soils within the
channel, measured at up to 3 locations

NM



Soil moisture and texture*

Extent of soil saturation and texture measured at
three locations in the channel

OTH



Woody jams

Number of woody jams within the channel

OTH

Biological indicators



Live and dead algal cover

Visual estimate of the percent of streambed
covered by live or dead algal growth

OTH



Filamentous algal abundance

Estimate of the overall abundance of filamentous
algae within the channel

NM



Stream shading

Percent shade-providing cover above the
streambed measured with a densiometer at
three locations

OTH



Hydrophytic plant species

Number of OBL or FACW-rated plants (as listed in
Lichvar et al. 2016) growing within the channel or
one half-channel width from the channel

PNW



Fish

Estimate of the overall abundance offish (other
than non-native mosquitofish) in the channel.

NM



Aquatic invertebrates

Abundance and richness of aquatic invertebrate
families collected from the channel

PNW



Aquatic invertebrates

Estimate of the overall abundance of aquatic
invertebrates within the channel

NM



Amphibians

Estimate of the overall abundance of amphibians
within the channel

NM



Mosses and liverworts

Visual estimate of the percent of streambed and
banks covered by live or dead bryophytes or
liverworts

OTH



Differences in vegetation
(riparian corridor)

Visual estimate of the distinctiveness of
vegetation in the riparian corridor compared to
surrounding upland vegetation

NM



Absence of upland rooted
plants in the streambed

Visual estimate of the extent of upland rooted
plants growing within the streambed

NM

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Candidate indicator

Description

Origin



Presence of iron-oxidizing
fungi or bacteria

Presence of oily sheens indicative of iron-
oxidizing fungi or bacteria within the assessment
reach

NM



Presence of aquatic or semi-
aquatic snakes

Presence of aquatic or semi-aquatic snakes (e.g.,
most garter snake species) in the channel

PNW

Geospatial indicators



Elevation

Elevation above mean sea level

OTH



Long-term normal
precipitation and
temperature

30-y normal mean annual and monthly
precipitation, and 30-y normal mean, maximum,
and minimum annual temperature (PRISM
climate data; Hart and Bell 2015).

OTH



Strata (location)

The four subregions or 'strata' into which the
Northern and Southern Great Plains have been
subdivided: Northern Prairie, Central Prairie,
Upper Midwest, and Southern Plains

OTH



Baseflow Index (BFI)

The ratio of baseflow to total flow, expressed as
a percentage and provided as a 1-kilometer
raster grid for the conterminous U.S. (Wolock,
2003)

OTH

Candidate Reach Identification and Data Collection

We had two objectives in selecting candidate reaches for this study: first, to include a sufficient
number of reaches in each streamflow duration class to characterize variability in indicator
measurements; and second, to select reaches representing the range of key natural and
disturbance gradients within the GP to support applicability of the method across anticipated
conditions. To support our goal of geographic representativeness, we subdivided the Northern
GP into 3 subregions or strata, based on EPA Level II Ecoregion boundaries (Omernik 1995). This
resulted in 4 strata: Central Prairie, Northern Prairie, Upper Midwest, and Southern Great
Plains. We aimed to select 290 stream-reaches (one assessed location per reach) with equal
representation of perennial, intermittent, and ephemeral flow duration classes among and
within the four GP strata (Figure 3).

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To screen reaches for use iri method
development, we first compiled a list
of 3566 candidate study reaches
based on existing hydrologic data
records (e.g., U.S. Geological Survey
(USGS) stream gages, water presence
loggers, wildlife cameras, field
photos), published studies, and
interviews with local experts familiar
with the specific reach's hydrology.

Most of these reaches (2945) were
derived from the database of stream
gages operated by the USGS and
2298 (78%) of them were perennial.

(Actual streamflow duration class
was determined by applying the
flowchart in Figure 4, which was
informed by existing definitions
(Hedman and Osterkamp 1982,

Hewlett 1982).) Consequently, other
sources were required to identify
candidate ephemeral and
intermittent reaches. Another 621
candidate study reaches were

Figure 3: The four GP sub-strata; study reaches shov
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r

DOR >328

Insufficient
record

Yes

*¦ Zyear <37

Zyear >328

Myear > 37

Unclassified